Method, device and program for measuring image quality adjusting ability, and method, device and program for adjusting image quality

ABSTRACT

An image quality adjustment capability measurement method includes the steps of: using an instructor image serving as a target for the image qualities of an evaluation image and a correlation function between image quality characteristic differences and image quality adjustment capability values, the instructor image and the correlation function being obtained in advance; inputting a corrected image obtained after the image qualities of the evaluation image is adjusted; calculating the image quality characteristic difference between the input corrected image and the instructor image; and calculating the image quality adjustment capability value from the correlation function between the image quality characteristic differences and the image quality adjustment capability values, which is obtained in advance, and the calculated image quality characteristic difference.

TECHNICAL FIELD

The present invention relates to an image quality adjustment capabilitymeasurement method, device and program, and an image quality adjustmentmethod, device and program. The present invention particularly relatesto an image quality adjustment capability measurement method, device andprogram that measure the image qualities of color images adjusted by aperson or color image system, which a person subjectively perceives, asan objective value. Moreover, the present invention relates to an imagequality adjustment method, device and program that are based on anobjective value representing the image quality adjustment capability ofa person or color image system. Furthermore, the present inventionrelates to an image quality adjustment capability training method,device and program that are based on an objective value representing theimage quality adjustment capability of a person or color image system.

BACKGROUND ART

In a color image device or color image processing system, the imagequalities of color images are an extremely important factor. Therefore,careful setting is necessary for the image quality of color imagesrealized by the color image device or color image processing system.Here, the focus is put on such image qualities as brightness of anentire image, gamma characteristics, and sharpness, which can bearbitrarily adjusted by image processing, not on such image qualities asthe physically determined limit values of white or black in brightnessor density and the color gamut of devices, which are attributable tohardware characteristics. The image qualities represent the capabilityand characteristics of the color image device or color image processingsystem. Therefore, setting of the image qualities is an extremelyimportant factor.

Now the setting of such image qualities is performed primarily based onthe detailed evaluation and adjustment of image qualities by engineers.According to the method, the image qualities set in the color imagedevice or color image system are mostly affected by the skill(capability) of a person who makes sure of the image qualities of colorimages in the color image device or color image system to adjust theimage qualities. That is, in the color image device or color imageprocessing system, an engineer who has a high capability in adjustingimage qualities is required in order to appropriately stabilize theimage qualities as expected.

These days, various kinds of color image devices, such as PDP (PlasmaDisplay Panel), LCD (Liquid Crystal Display), printers, camera-equippedcellular phones, and projectors, are put into the market. When just onecomponent used to form an image is replaced in a device, the imagequalities change. Therefore, the adjustment of image qualities isperformed each time the component is replaced. Moreover, even if theconfiguration of components is the same, the image qualities to beexpressed may change according to type of device. Even if the type ofdevice is the same, there may be a plurality of image quality modes. Ineach case, the adjustment of image qualities is necessary.

A completely automated method for adjustment or setting of imagequalities or designing thereof has not yet been realized. Therefore, inorder to put various kinds of such color image devices into the market,it is necessary to have many engineers who have high capabilities inadjusting image qualities. However, it takes enormous time and effortsto improve people's image quality adjustment capabilities because thetechnique is learned through the actual work of adjusting imagequalities. Accordingly, it is effectively impossible to gather manyengineers who have high capabilities in adjusting image qualities in ashort period of time. Therefore, the adjustment of image qualities ofcolor image devices, the various types of which are increasingly putinto the market, is currently performed by a small number of engineerswho spend much energy and production processes for the adjustment.

The following Patent Documents 1 and 2 disclose conventional artsrelated to the above-described image processing.

Patent Document 1 proposes an image processing device that includes aninput section, an instructor data extraction section, a correctionsection, and an image processing section in order to intuitively andeasily convey favorite image reproduction to the image processing deviceso that the favorite image reproduction is reflected in the imageprocess. The image processing device operates in the following manner:The input section accepts the input instruction of a target image (aninstructor image) for image reproduction in the image process; theinstructor data extraction section performs analysis or informationcollection for the predetermined image reproduction items for theinstructor image provided, and extracts instructor data representing thetendency of image reproduction; the correction section correctsparameters of the image process in accordance with the tendency of imagereproduction represented by the instructor data; the image processingsection performs the image process for the input image using thecorrected parameters.

Patent Document 2 proposes an image processing device that includes apreliminary correction section, an amount-of-characteristic calculationsection, a correction value calculation section, and a correctionexecution section in order to efficiently perform image qualities of thecorrected image of each image among a group of images. The imageprocessing device operates in the following manner: The preliminarycorrection section preliminarily corrects a sample image among a groupof images and obtains the preliminarily corrected image of the sampleimage; the amount-of-characteristic calculation section calculates theamount of characteristic of each preliminarily corrected image; thetarget-amount-of-characteristic calculation section calculates thetarget amount of characteristic such that the variation between thetarget amount of characteristic and the amount of characteristic of eachpreliminarily corrected image is minimized; the correction valuecalculation section calculates a correction value of each image suchthat the amount of characteristic of each image of the group of imagesis equal to the target amount of characteristic; the correctionexecution section uses the correction value to correct the correspondingimage.

Patent Document 1: JP-A-2006-080746

Patent Document 2: JP-A-2006-139368

Non-Patent Document 1: Masato Tsukada, Tetsuaki Suzuki, and Akira Inoue,“Automated technique for improving image qualities in digital imageprocessing”, Journal of the Imaging Society of Japan, 2004, Vol. 43, No.2, pp. 90-97

SUMMARY OF INVENTION Technical Problem

However, the above-mentioned conventional arts have the followingchallenges.

1) The image qualities of the color image device or color image systemdepend on the image adjustment capability of the person or color imagesystem performing the adjustment. Accordingly, the first challenge is toestablish an image quality adjustment capability measurement method toobjectively evaluate the image quality adjustment capability of theperson or color image system performing adjustment, in order to obtainthe more stabilized image qualities of the color image device or colorimage system.

2) The second challenge is to automatically adjust the image qualitiesset in the color image device or color image system to the desired imagequalities which a person subjectively perceives.

3) The third challenge is to objectively evaluate the level ofperformance of the image qualities and present the level when the imagequalities set in the color image device or color image system areautomatically adjusted to the desired image qualities which a personsubjectively perceives.

4) The fourth challenge is to train the image adjustment capability of aperson who adjusts the image qualities of the color image device orcolor image system in accordance with an objective image qualityadjustment capability value.

The above challenges are not recognized in the above-mentioned PatentDocuments 1 and 2.

An object of the present invention is to provide an image qualityadjustment capability measurement method, device and program which canobjectively evaluate the image adjustment capability of a person orcolor image system for a color image device and a color image processingsystem.

Another object of the present invention is to provide an image qualityadjustment method, device and program which can automatically adjust theimage qualities for the color image device and the color imageprocessing system in accordance with the above image quality adjustmentcapability measurement method.

Another object of the present invention is to provide an image qualityadjustment capability training method, device and program which cantrain the image adjustment capability of a person for the color imagedevice and the color image processing system.

Solution to Problem

According to the present invention, a first image quality adjustmentcapability measurement method includes the steps of: using an instructorimage serving as a target for the image qualities of an evaluation imageand a correlation function between image quality characteristicdifferences and image quality adjustment capability values, theinstructor image and the correlation function being obtained in advance;inputting a corrected image obtained after the image qualities of theevaluation image are adjusted; calculating the image qualitycharacteristic difference between the corrected image and the instructorimage; and calculating the image quality adjustment capability valuefrom the correlation function and the image quality characteristicdifference.

Moreover, according to the first image quality adjustment capabilitymeasurement method of the present invention, using the instructor imageand the correlation function may mean: using the evaluation image, afirst corrected image obtained after the image qualities of theevaluation image are adjusted and evaluated in terms of subjective imagequality, and an instructor image serving as a target for the imagequalities of the evaluation image, the evaluation image, the firstcorrected image, and the instructor image being obtained in advance;calculating the image quality adjustment capability value for the firstcorrected image the subjective image qualities of which are evaluated;calculating the image quality characteristic difference between thefirst corrected image and the instructor image; and using a correlationfunction between the image quality characteristic difference and theimage quality adjustment capability value calculated from the imagequality characteristic difference and the image quality adjustmentcapability value.

Furthermore, according to the present invention, a second image qualityadjustment capability measurement method includes the steps of: using afirst corrected image obtained after the image qualities of theevaluation image are adjusted and evaluated in terms of subjective imagequality and an instructor image serving as a target for the imagequalities of the evaluation image, the first corrected image and theinstructor image being obtained in advance; calculating an image qualityadjustment capability value for the first corrected image; calculatingan image quality characteristic difference between the first correctedimage and the instructor image, and acquiring a correlation functionbetween the image quality characteristic difference and the imagequality adjustment capability value; acquiring a second corrected imageby letting a user whose image quality adjustment capability is to bemeasured adjust the image qualities of the evaluation image; andcalculating the image quality characteristic difference between thesecond corrected image and the instructor image, and calculating theuser's image quality adjustment capability value from the correlationfunction and the image quality characteristic difference.

Furthermore, according to the present invention, a third image qualityadjustment capability measurement method includes the steps of:acquiring a first corrected image obtained after the image qualities ofa plurality of evaluation images are adjusted; performing subjectiveevaluation on the image qualities of the first corrected image;calculating an image quality adjustment capability value from the resultof subjective evaluation on the image qualities of the first correctedimage; calculating the image quality characteristic difference betweenthe first corrected image and an instructor image serving as a targetfor the image qualities of the evaluation image, and acquiring acorrelation function between the image quality characteristic differenceand the image quality adjustment capability value; acquiring a secondcorrected image by letting a user adjust the image qualities of theevaluation image; and calculating the image quality characteristicdifference between the second corrected image and the instructor image,and calculating the user's image quality adjustment capability valuefrom the correlation function and the image quality characteristicdifference.

According to the present invention, a first image quality adjustmentcapability measurement device includes: a section that uses a givencorrelation function between image quality characteristic differencesand image quality adjustment capability values; a corrected image inputsection that inputs a corrected image obtained after the image qualitiesof an evaluation image are adjusted; an instructor image storage memorythat stores an instructor image serving as a target for the imagequalities of the evaluation image; an image quality characteristicdifference calculation section that calculates the image qualitycharacteristic difference between the corrected image and the instructorimage; and an image quality adjustment capability determination sectionthat calculates the image quality adjustment capability value from thecorrelation function and the image quality characteristic difference.

Moreover, according to the present invention, a second image qualityadjustment capability measurement device includes: a section that uses agiven correlation function between image quality characteristicdifferences and image quality adjustment capability values; anevaluation image storage memory that stores an evaluation image; animage processing section that generates a corrected image by letting auser whose image quality adjustment capability is to be measured adjustthe image qualities of the evaluation image; an image presentationsection that presents the evaluation image and the corrected image tothe user; an instructor image storage memory that stores an instructorimage serving as a target for the image qualities of the evaluationimage; an image quality characteristic difference calculation sectionthat calculates the image quality characteristic difference between thecorrected image and the instructor image; and an image qualityadjustment capability determination section that calculates the user'simage quality adjustment capability value from the correlation functionand the image quality characteristic difference.

According to the present invention, an image quality adjustment methodincludes the steps of: using a given evaluation image, a giveninstructor image serving as a target for the image qualities of theevaluation image, and a given correlation function between image qualitycharacteristic differences and image quality adjustment capabilityvalues; generating correction parameters used in an image process tocorrect the image qualities of the evaluation image; generating acorrected image by performing the image process for the evaluation imageusing the correction parameters; calculating the image qualitycharacteristic difference between the corrected image and the instructorimage; determining target correction parameters from the correctionparameters using the image quality characteristic difference and thecorrelation function to obtain the desired image qualities; andcorrecting the image qualities of an arbitrarily input image using theimage process and the target correction parameters.

Moreover, according to the image quality adjustment method of thepresent invention, determining the target correction parameters mayinclude setting a target value for adjusting the desired imagequalities.

According to the present invention, an image quality adjustment deviceincludes: a section that uses a given correlation function between imagequality characteristic differences and image quality adjustmentcapability values; an evaluation image storage memory that stores anevaluation image; a correction parameter generation section thatgenerates correction parameters used in an image process to adjust theimage qualities of the evaluation image; an image processing sectionthat generates a corrected image by performing the image process for theevaluation image using the correction parameters; an instructor imagestorage memory that stores an instructor image serving as a target forthe image qualities of the evaluation image; an image qualitycharacteristic difference calculation section that calculates the imagequality characteristic difference between the corrected image and theinstructor image; a target correction parameter determination sectionthat determines target correction parameters from the correctionparameters using the image quality characteristic difference and thecorrelation function to obtain the desired image qualities; and an imagecorrection section that corrects the image qualities of an arbitrarilyinput image using the image process and the target correctionparameters.

Moreover, according to the image quality adjustment device of thepresent invention, the target correction parameter determination sectionincludes a section that sets a target value for adjusting the desiredimage qualities.

According to the present invention, a first image quality adjustmentcapability measurement program causes a computer to execute: a processof using a given correlation function between image qualitycharacteristic differences and image quality adjustment capabilityvalues; a process of inputting a corrected image obtained after theimage qualities of an evaluation image is adjusted; a process of storingan instructor image serving as a target for the image qualities of theevaluation image; a process of calculating the image qualitycharacteristic difference between the corrected image and the instructorimage; and a process of calculating the image quality adjustmentcapability value from the correlation function between the image qualitycharacteristic differences and the image quality adjustment capabilityvalues and the image quality characteristic difference.

Moreover, according to the present invention, a second image qualityadjustment capability measurement program causes a computer to execute:a process of using a given correlation function between image qualitycharacteristic differences and image quality adjustment capabilityvalues; a process of storing an evaluation image; an image process ofgenerating a corrected image by letting a user whose image qualityadjustment capability is to be measured adjust the image qualities ofthe evaluation image; a process of presenting the evaluation image andthe corrected image to the user; a process of allowing the user tocontrol parameters used in the image process; a process of storing aninstructor image serving as a target for the image qualities of theevaluation image; a process of calculating the image qualitycharacteristic difference between the corrected image and the instructorimage; and a process of calculating the user's image quality adjustmentcapability value from the correlation function and the image qualitycharacteristic difference.

According to the present invention, an image quality adjustment programcauses a computer to execute: a process of using a given correlationfunction between image quality characteristic differences and imagequality adjustment capability values; a process of storing an evaluationimage; a process of generating correction parameters used in an imageprocess to adjust the image qualities of the evaluation image; a processof generating a corrected image by performing the image process for theevaluation image using the correction parameters; a process of storingan instructor image serving as a target for the image qualities of theevaluation image; a process of calculating the image qualitycharacteristic difference between the corrected image and the instructorimage; a process of determining target correction parameters from thecorrection parameters using the image quality characteristic differenceand the correlation function to obtain the desired image qualities; anda process of correcting the image qualities of an arbitrarily inputimage using the image process and the target correction parameters.

Moreover, according to the image quality adjustment program of thepresent invention, the process of determining the target correctionparameters may include a process of setting a target value for adjustingthe desired image qualities.

According to the present invention, a first image quality adjustmentcapability training method includes the steps of: using an instructorimage serving as a target for the image qualities of an evaluation imageand a correlation function between image quality characteristicdifferences and image quality adjustment capability values, theinstructor image and the correlation function being obtained in advance;acquiring a corrected image by letting a user whose image qualityadjustment capability is to be measured adjust the image qualities ofthe evaluation image; calculating the image quality characteristicdifference between the corrected image and the instructor image, andcalculating the user's image quality adjustment capability value fromthe correlation function and the image quality characteristicdifference; and controlling an image quality adjustment operation inwhich the user adjusts the image qualities of the evaluation image toobtain the corrected image.

According to the present invention, a second image quality adjustmentcapability training method includes the steps of: using a firstcorrected image obtained after the image qualities of an evaluationimage are adjusted and evaluated in terms of subjective image qualityand an instructor image serving as a target for the image qualities ofthe evaluation image, the first corrected image and the instructor imagebeing obtained in advance; calculating an image quality adjustmentcapability value for the first corrected image evaluated in terms of thesubjective image quality; calculating an image quality characteristicdifference between the corrected image and the instructor image, andacquiring a correlation function between the image qualitycharacteristic difference and the image quality adjustment capabilityvalue; acquiring a second corrected image by letting a user whose imagequality adjustment capability is to be measured adjust the imagequalities of the evaluation image; calculating the image qualitycharacteristic difference between the second corrected image and theinstructor image, and calculating the user's image quality adjustmentcapability value from the correlation function and the image qualitycharacteristic difference; and controlling an image quality adjustmentoperation in which the user adjusts the image qualities of theevaluation image to obtain the second corrected image.

According to the present invention, an image quality adjustmentcapability training device includes: a section that uses a givencorrelation function between image quality characteristic differencesand image quality adjustment capability values; an evaluation imagestorage memory that stores an evaluation image; an image processingsection that generates a corrected image by letting a user whose imagequality adjustment capability is to be measured adjust the imagequalities of the evaluation image; an instructor image storage memorythat stores an instructor image serving as a target for the imagequalities of the evaluation image; an image quality characteristicdifference calculation section that calculates the image qualitycharacteristic difference between the corrected image and the instructorimage; an image quality adjustment capability determination section thatcalculates the user's image quality adjustment capability value from thecorrelation function and the image quality characteristic difference;and an image quality adjustment operation control section that controlsan image quality adjustment operation in which the user adjusts theimage qualities of the evaluation image to generate the corrected image.

According to the present invention, an image quality adjustmentcapability training program causes a computer to execute: a process ofusing a given correlation function between image quality characteristicdifferences and image quality adjustment capability values; a process ofstoring an evaluation image; an image process of generating a correctedimage by letting a user whose image quality adjustment capability is tobe measured adjust the image qualities of the evaluation image; aprocess of presenting the evaluation image and the corrected image tothe user; a process of allowing the user to control parameters used inthe image process; a process of storing an instructor image serving as atarget for the image qualities of the evaluation image; a process ofcalculating the image quality characteristic difference between thecorrected image and the instructor image; a process of calculating theuser's image quality adjustment capability value from the correlationfunction and the image quality characteristic difference; and a processof controlling an image quality adjustment operation in which the useradjusts the image qualities of the evaluation image to generate thecorrected image.

ADVANTAGEOUS EFFECTS OF INVENTION

The first effect of the present invention is to be able to objectivelymeasure the capability of a person or color image system in adjustingthe image qualities of color images for a color image device and a colorimage processing system.

The second effect of the present invention is to be able toautomatically adjust the image qualities set in the color image deviceand the color image processing system to the desired image qualitieswhich a person subjectively perceives.

The third effect of the present invention is to be able to automaticallyadjust the image qualities set in the color image device and the colorimage processing system to the desired image qualities which a personsubjectively perceives and furthermore to present the level ofperformance of the image qualities at that time.

The fourth effect of the present invention is to be able to train theimage adjustment capability of a person who adjusts the image qualitiesof color images for the color image device and the color imageprocessing system.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a flowchart illustrating the operation of an image qualityadjustment capability measurement method according to a first exemplaryembodiment of the present invention.

FIG. 2 is a diagram illustrating an example of a GUI of an imageprocessing tool for correcting the image qualities of an evaluationimage.

FIG. 3 is a diagram illustrating a user adjusting the image qualities ofthe presented evaluation image using an image quality adjustment GUI ofthe image processing tool.

FIG. 4 is a diagram illustrating an example of relation between imagequality characteristic differences and image quality adjustmentcapability values.

FIG. 5 is a diagram illustrating a correlation function calculated fromthe example of relation between image quality characteristic differencesand image quality adjustment capability values.

FIG. 6 is a block diagram illustrating the overall configuration of animage quality adjustment capability measurement device according to asecond exemplary embodiment of the present invention.

FIG. 7 is a flowchart illustrating the operation of an image qualityadjustment capability measurement device according to a third exemplaryembodiment of the present invention.

FIG. 8 is a flowchart illustrating the operation of an image qualityadjustment method according to a fourth exemplary embodiment of thepresent invention.

FIG. 9 is a block diagram illustrating the overall configuration of animage quality adjustment device according to a fifth exemplaryembodiment of the present invention.

FIG. 10 is a flowchart illustrating the operation of an image qualityadjustment method according to a sixth exemplary embodiment of thepresent invention.

FIG. 11 is a block diagram illustrating the overall configuration of animage quality adjustment device according to a seventh exemplaryembodiment of the present invention.

FIG. 12 is a flowchart illustrating the operation of an image qualityadjustment capability training method according to an eighth exemplaryembodiment of the present invention.

FIG. 13 is a block diagram illustrating the overall configuration of animage quality adjustment capability training device according to a ninthexemplary embodiment of the present invention.

EXPLANATION OF REFERENCE SYMBOLS

-   1: Evaluation image storage memory-   2: Image processing section-   3: Image presentation section-   4: Parameter control section-   5: Instructor image storage memory-   6: Image quality characteristic difference calculation section-   7: Image quality adjustment capability determination section-   8: Correction parameter generation section-   9: Corrected image storage memory-   10: Optimum correction parameter determination section-   11: Image quality adjustment operation control section-   100, 101: Image quality adjustment capability measurement device-   102, 103: Image quality adjustment device-   104: Image quality adjustment capability training device-   200: Image processing tool-   300: User interface

DESCRIPTION OF EMBODIMENTS

The following describes exemplary embodiments of the present inventionwith reference to the accompanying diagrams.

First Exemplary Embodiment

FIG. 1 illustrates the procedure of an image quality adjustmentcapability measurement method according to a first exemplary embodimentof the present invention.

In FIG. 1, in order to measure the image quality adjustment capability,an evaluation image and an instructor image, which is a target for theevaluation image and has a good image quality, are prepared in advance(step ST1). Here, the evaluation image and the instructor image thereofinclude not only still images but moving images. For reasons ofconvenience, still and moving images are not distinguished from eachother and are referred to as images.

The evaluation image to be used includes a variety of images of naturalimages and CG (computer graphics) images, such as night scenes,landscapes, artificial materials, and portraits. A target instructorimage is necessary for each scene of the evaluation image. Theinstructor image includes an evaluation image corrected by an engineerhaving a high capability in adjusting image qualities with the use of animage processing tool and the like, and other images.

Then, according to the image quality adjustment capability measurementmethod of the first exemplary embodiment, a first corrected image isgenerated by letting many users subjectively adjust the image qualitiesof each scene of the evaluation image with the use of an imageprocessing tool or the like (step ST2).

FIG. 2 shows an example of an image processing tool to correct the imagequalities of the evaluation image.

The image processing tool 200 shown in FIG. 2 loads and displays theevaluation image, and also displays the first corrected image the imagequalities of which have been adjusted by a user. In the example of FIG.2, the image processing tool 200 has functions to correct basic imagequality factors such as brightness, saturation, contrast, sharpness,tone, and white balance, and a GUI (Graphical User Interface) thereof.However, the tool is not limited to the above factors. Other itemsnecessary for adjusting image qualities, such as noise suppression andcorrecting specific colors including a flesh color, green of trees andplants and a blue sky, can be added. The correction process of the imagequalities may be the correction process disclosed in Non-Patent Document1.

FIG. 3 illustrates a user adjusting the image qualities of the presentedevaluation image using the image quality adjustment GUI of the imageprocessing tool 200. Incidentally, the corrected image is presented tothe user at the same time after correction. The user similarly adjuststhe image qualities of all the evaluation images. The adjustment ofimage qualities of the evaluation images is performed by many users, andmany first corrected images are obtained.

The image qualities of the first corrected images produced by many usersare subjectively evaluated, and experimental data are obtained forlearning the image quality adjustment capabilities of users (step ST3).Each scene of the first corrected image obtained by the user's imagequality adjustment is evaluated in terms of image quality in accordancewith an image quality evaluation method such as a paired comparisonmethod. For example, out of a plurality of the first corrected images,the same scenes of two corrected images are selected at random andpresented to an evaluator who then chooses the one having better imagequalities. The evaluation of image qualities is performed for allcombinations. The evaluation experiments are conducted for a pluralityof evaluators, and enough data are collected for subjective evaluationexperiments. The data are necessary to learn the image qualityadjustment capabilities of users.

Then, based on the results of the subjective evaluation experiments onthe image qualities of the first corrected images, an image qualityadjustment capability value that represents the image quality adjustmentcapability of a user is calculated (step ST4).

For calculation of the image quality adjustment capability values, thefirst corrected images are ranked according to image qualities based onthe results of the subjective evaluation experiments on the imagequalities of the first corrected images. For example, the results ofimage quality evaluation experiments of the first corrected images arearranged in a table, and calculation is performed for the firstcorrected images, the image qualities of which have been adjusted byusers, to obtain a cumulative probability, which is the result ofsumming up the percentages of victories in paired comparison, or aninterval scale based on Thurstone's law of comparative judgment. Themagnitudes of the values represent whether the subjective imagequalities of the first corrected images are good or not. Such indicatorsas the cumulative probability and the interval scale can be regarded asan image quality adjustment capability value representing the imagequalities of the first corrected image, or the image quality adjustmentcapability of the user who have adjusted the image qualities of theevaluation image.

Incidentally, during calculation of the image quality adjustmentcapability value at step ST4, it becomes clear which image has the bestimage qualities for each scene. Accordingly, the first corrected imagehaving the best image qualities can be an instructor image for thescene.

Then, the difference in image quality characteristic between the firstcorrected image and the instructor image is calculated, the correlationfunction between the image quality characteristic difference and theimage quality adjustment capability value is obtained (step ST5). Here,the image quality characteristic difference includes the average ofdifferences in RGB Euclidean distance, the average of differences inlightness (the L value of CIELAB), the average of differences inbrightness (Y out of the tristimulus values XYZ), the average of colordifferences (Eab), and the average of differences in saturation (chroma(see below)).

Chroma=√{square root over ((a*)²+(b*)²)}{square root over((a*)²+(b*)²)}  [Math. 1]

For example, if the image quality characteristic difference between thecorrected image and the instructor image is the average of differencesin RGB Euclidean distance, the image quality characteristic differenceis represented as follows:

$\begin{matrix}\left\lbrack {{Math}.\mspace{14mu} 2} \right\rbrack & \; \\{{{Image}\mspace{14mu} {quality}\mspace{14mu} {characteristics}\mspace{14mu} {difference}} = {\left( {\sum\limits_{x,y}\sqrt{\begin{matrix}\begin{matrix}{\; {\left( {{T_{R}\left( {x,y} \right)} - {C_{R}\left( {x,y} \right)}} \right)^{2} +}} \\{\left( {{T_{G}\left( {x,y} \right)} - {C_{G}\left( {x,y} \right)}} \right)^{2} +}\end{matrix} \\\left( {{T_{B}\left( {x,y} \right)} - {C_{B}\left( {x,y} \right)}} \right)^{2}\end{matrix}}} \right)/\left( {x \cdot y} \right)}} & {{Equation}\mspace{14mu} (1)}\end{matrix}$

Here, x and y represent the coordinate position of the image, and TR,TG, and TB represent the pixel values R, G, and B of the instructorimage. CR, CG, and CB represent the pixel values R, G, and B of thefirst corrected image. Σ means adding up the differences of RGBEuclidean distance of all the pixels of the image. Here, the imagequality characteristic difference may be calculated from the entireimage as described above or from a predetermined attention area. If TR,TG, TB, CR, CG, and CB are respectively replaced with L*, a*, and b* ofCIELAB, the image quality characteristic difference is the average ofcolor differences. As for the differences in saturation or lightness,the differences in saturation or lightness are similarly calculatedbetween the first corrected image and the instructor image.

Moreover, the difference information of histograms related to such colorinformation as contrast ratio, saturation, lightness, brightness, orhues, and the difference in the amount of edges can be used as an imagequality characteristic difference. In the typical correction ofcontrast, a histogram is created for the brightness components of theimage, several percent of candidates are removed from the upper andlower sides of the histogram as noise component, and the High value ofthe Highlight component of the image and the Low value of the Shadowcomponent are extracted. For example, if the contrast of the image isCont, the contrast Cont of the image is defined as follows:

[Math. 3]

Cont=Hight−Low  Equation (2)

Here, assume that the contrast ratio is Cont_Ratio, the contrast of theinstructor image of a certain scene is Cont_Best, and the contrast ofthe corrected image X is Cont_X. In this case, as represented in thefollowing equation, the contrast ratio Cont_Ratio can be calculated fromthe ratio of the contrast Cont_Best of the instructor image to thecontrast Cont_X of the corrected image X.

[Math. 4]

Cont_Ratio=Cont_X/Cont_Best  Equation (3)

Moreover, the histograms related to such color information asbrightness, lightness, hues, and saturation are evaluated based on thedifferences in shape of the histograms. For example, assume that in acertain scene, the brightness histogram of the instructor image isYhist_Best(i) and the brightness histogram of the first corrected imageX is Yhist_X(i). Here, i represents an element of a histogram array: imay be 0 to 255 in the case of brightness. If the evaluation value ofthe difference between the brightness histogram Yhist_Best(i) of theinstructor image and the brightness histogram Yhist_X(i) of the firstcorrected image X is Yhist_diff_X, the evaluation value Yhist_diff_X isdefined as follows:

[Math. 5]

Yhist _(—) diff _(—) X=ΣABS(Yhist _(—) Best(i)−Yhist _(—)X(i))  Equation (4)

Here, ABS( ) is a function representing an absolute value. Calculationis also performed for the chroma histograms of saturation, brightness,and hues for each color attribute in a similar way to the brightnesshistogram.

As described above, the image quality characteristic difference includesthe average of differences in RGB Euclidean distance, the average ofdifferences in lightness (the L value of CIELAB), the average ofdifferences in brightness (Y out of the tristimulus values XYZ), theaverage of color differences (Eab), the average of differences insaturation, the difference information of histograms related to suchcolor information as contrast ratio, saturation, lightness, brightness,or hues, and the difference in the amount of edges. However, the imagequality characteristic difference is not limited to these kinds ofinformation. Various kinds of difference information between the firstcorrected image and the instructor image can be used.

FIG. 4 is an example in which the image quality characteristicdifferences D (color differences) that are each given to each firstcorrected image and the image quality adjustment capability values S(cumulative probabilities) are plotted, with the vertical axisrepresenting the image quality characteristic differences and thehorizontal axis representing the image quality adjustment capability. Itis clear from what are plotted in FIG. 4 that there is a correlationbetween the image quality characteristic differences D and the imagequality adjustment capability values S. Therefore, the correlationfunction S=Fc(D) between the image quality characteristic differences Dand the image quality adjustment capability values S is calculated.

Then, as illustrated in FIG. 3, a second corrected image is obtained byletting a user, whose image quality adjustment capability is to bemeasured, correct the image qualities of the evaluation image using animage processing tool that can control the strength of correction amongthe image quality items of the image (step ST6).

Then, the image quality characteristic difference D between the secondcorrected image and the instructor image is calculated. With the use ofthe image quality characteristic difference D and the correlationfunction (S=Fc(D)) obtained at step ST5, the image quality adjustmentcapability value S of the user is determined (step ST7). The imagequality adjustment capability value S is output (step ST8).

For example, FIG. 5 is a diagram showing the correlation functionS=Fc(D) calculated from the correlation between the image qualitycharacteristic differences S and the image quality adjustment capabilityvalues D illustrated in FIG. 4. As shown in FIG. 5, if the average ofthe color difference, or the image quality characteristic difference S,of the second corrected image obtained after the user has adjusted theimage qualities of the evaluation image of a certain scene and theinstructor image of the scene is 3, the user's image quality adjustmentcapability value D calculated from the correlation function S=Fc(D) isabout 2.5. In the case of FIG. 5, the highest value of the image qualityadjustment capability value D is around 3.5. Therefore, it can beconcluded that the user's image quality adjustment capability isrelatively high.

Therefore, according to the present exemplary embodiment, the imagequality adjustment capability of a user for color images of the colorimage device and the color image processing system can be measuredobjectively.

Incidentally, according to the present invention, the image qualityadjustment capability of a user (a person) is measured. However, thepresent invention is not limited to this. The image quality adjustmentcapability of a color image system may be measured. In this case, theimage quality adjustment capability of the color image system for colorimages of the color image device and the color image processing systemcan be measured objectively.

Second Exemplary Embodiment

The following describes an image quality adjustment capabilitymeasurement device 100 according to a second exemplary embodiment of thepresent invention, with reference to FIG. 6.

FIG. 6 is a block diagram illustrating the image quality adjustmentcapability measurement device 100 according to the present exemplaryembodiment. The image quality adjustment capability measurement device100 shown in the diagram uses the image quality adjustment capabilitymeasurement method of the first exemplary embodiment, and is a devicethat lets a user adjust the image qualities of the image through an userinterface 300 such as the above-mentioned GUI of the image processingtool 200 to output the image quality adjustment capability value, whichis an objective evaluation value of the image quality adjustmentcapability of the user.

The image quality adjustment capability measurement device 100 includesan evaluation image storage memory 1, an image processing section 2, animage presentation section 3, a parameter control section 4, aninstructor image storage memory 5, an image quality characteristicdifference calculation section 6, and an image quality adjustmentcapability determination section 7.

The evaluation image storage memory 1 stores the evaluation image. Theimage processing section 2 performs an image process to adjust the imagequalities of the evaluation image and produces the corrected image. Theimage presentation section 3 presents the evaluation image and thecorrected image to a user. The parameter control section 4 can controlcorrection strength parameters of an image quality correction processwhich the image processing section 2 performs while the user is watchingthe evaluation image and the corrected image. The instructor imagestorage memory 5 stores the instructor image, which is a target for theevaluation image. The image quality adjustment capability determinationsection 7 calculates the user's image quality adjustment capabilityvalue from the image quality characteristic difference and the imagequality characteristic difference calculation section 6 that calculatesthe image quality characteristic difference between the corrected imageand the instructor image.

The image quality adjustment capability measurement device 100 can berealized by a computer. The components constituting the image qualityadjustment capability measurement device 100, including the evaluationimage storage memory 1, the image processing section 2, the imagepresentation section 3, the parameter control section 4, the instructorimage storage memory 5, the image quality characteristic differencecalculation section 6, and the image quality adjustment capabilitydetermination section 7, can be realized as a program that theprocessing unit of the computer (CPU: Central Processing Unit) executesto realize the above-mentioned functions. The components constitutingthe image quality adjustment capability measurement device 100 can berealized by a computer and as a program.

The following describes the operation of the image quality adjustmentcapability measurement device 100.

First, the image quality adjustment capability measurement device 100stores in advance the evaluation image and the instructor image, whichis a target for the evaluation image, in the evaluation image storagememory 1 and the instructor image storage memory 5, respectively.

Then, the image presentation section 3 presents the evaluation imagestored in the evaluation image storage memory 1 to the user through theuser interface 300 as displayed on the above-mentioned GUI of the imageprocessing tool 200 in FIG. 2, as well as the image processing items foradjusting image qualities which have been prepared in the imageprocessing section 2. Incidentally, before the image processing isapplied, the portion for the corrected image of the GUI illustrated inFIG. 2 displays the evaluation image or nothing. The user selects thepresented image processing items to adjust the image qualities of thepresented evaluation image through the user interface 300.

Then, the parameter control section 4 presents the image qualityadjustment GUI of the image processing tool 200, as illustrated in FIG.3, to the user through the user interface 300, allowing the user tocontrol the strength of the correction parameter used in the selectedimage process. Therefore, the correction parameter specified by the useris output from the parameter control section 4 to the image processingsection 2.

Subsequently, the image processing section 2 performs the selected imageprocess for the evaluation image stored in the evaluation image storagememory 1 using the correction parameter which the user has specifiedthrough the parameter control section 4 to produce the corrected image,and outputs the corrected image to the image presentation section 3 topresent the corrected image to the user through the user interface 300.The image processing section 2 also outputs the corrected image to theimage quality characteristic difference calculation section 6.

Then, using, for example, the method of the equation (1) or the like,the image quality characteristic difference calculation section 6calculates the image quality characteristic difference D between theinstructor image corresponding to the evaluation image stored in advancein the instructor image storage memory 5 and the corrected image outputby the image processing section 2 in accordance with step ST4 in theabove-described image quality adjustment capability measurement method,and then outputs the image quality characteristic difference D to theimage quality adjustment capability determination section 7.

Subsequently, using the correlation function S=FC(D) between the imagequality characteristic difference D and the image quality adjustmentcapability value S prepared in advance in accordance with step ST5 inthe image quality adjustment capability measurement method of the firstexemplary embodiment, the image quality adjustment capabilitydetermination section 7 calculates the image quality adjustmentcapability value S for the image quality characteristic difference Dsupplied from the image quality characteristic difference calculationsection 6, and then outputs an image quality adjustment capability valueas the user's image quality adjustment capability value.

Therefore, according to the present exemplary embodiment, like the firstexemplary embodiment, the image quality adjustment capability of a userfor color images of the color image device and the color imageprocessing system can be measured objectively.

Incidentally, according to the present invention, the image qualityadjustment capability of a user (a person) is measured. However, thepresent invention is not limited to this. The image quality adjustmentcapability of a color image system may be measured. In this case, theimage quality adjustment capability of the color image system for colorimages of the color image device and the color image processing systemcan be measured objectively.

Third Exemplary Embodiment

The following describes an image quality adjustment capabilitymeasurement device 101 according to a third exemplary embodiment of thepresent invention, with reference to FIG. 7.

FIG. 7 is a block diagram illustrating the image quality adjustmentcapability measurement device 101 according to the present exemplaryembodiment. The image quality adjustment capability measurement device101 shown in the diagram includes an instructor image storage memory 5,which stores the instructor image, a target for the evaluation image; animage quality characteristic difference calculation section 6, whichcalculates the image quality characteristic difference between thecorrected image and the instructor image; and an image qualityadjustment capability determination section 7, which calculates theuser's image quality adjustment capability value from the calculatedimage quality characteristic difference.

That is, according to the present exemplary embodiment, the evaluationimage storage memory 1, the image processing section 2, the imagepresentation section 3, and the parameter control section 4 are omittedfrom the above-described image quality adjustment capability measurementdevice 100 shown in FIG. 6.

The image quality adjustment capability measurement device 101 loads thecorrected image which is obtained after the user corrects the imagequalities of the evaluation image, and outputs the user's image qualityadjustment capability value. The operation of each section constitutingthe image quality adjustment capability measurement device 101 is thesame as that of each section of the image quality adjustment capabilitymeasurement device 100.

The image quality adjustment capability measurement device 101 can berealized by a computer. The components constituting the image qualityadjustment capability measurement device 101, including the instructorimage storage memory 5, the image quality characteristic differencecalculation section 6, and the image quality adjustment capabilitydetermination section 7, can be realized as a program that theprocessing unit of the computer (CPU) executes to realize theabove-mentioned functions. The components constituting the image qualityadjustment capability measurement device 101 can be realized by acomputer and as a program.

Therefore, according to the present exemplary embodiment, like thesecond exemplary embodiment, the image quality adjustment capability ofa user for color images of the color image device and the color imageprocessing system can be measured objectively.

Incidentally, according to the present invention, the image qualityadjustment capability of a user (a person) is measured. However, thepresent invention is not limited to this. The image quality adjustmentcapability of a color image system may be measured. In this case, theimage quality adjustment capability of the color image system for colorimages of the color image device and the color image processing systemcan be measured objectively.

Fourth Exemplary Embodiment

The following describes an image quality adjustment method according toa fourth exemplary embodiment of the present invention, with referenceto FIG. 8. The image quality adjustment capability measurement method ofthe first exemplary embodiment is applied to the image qualityadjustment method, which is a method to automatically produce theoptimum correction parameters (target correction parameters) used toadjust the image qualities of the color image device or color imagesystem to the desired image qualities which a person subjectivelyperceives.

In FIG. 8, like the image quality adjustment capability measurementmethod of the first exemplary embodiment, the evaluation image and theinstructor image, which is a target for the evaluation image and has agood image quality, are prepared in advance (step ST11).

Then, correction parameters that are to be used in an image process tocorrect the image qualities of the evaluation image is generated (stepST12). Here, a function for the image process of the evaluation image Iis represented as P(I, a, b). In this case, a and b are parameters tocontrol the strength of the image process, and are real numbers. At stepST12, numbers are selected from a group of numbers which can be a and b,and the selected numbers are regarded as correction parameters.

Subsequently, the corrected image of the evaluation image I is generatedwith the image process function P (I, a, b) using the correctionparameters a and b generated at step ST12. (step ST13). Then, with theuse of, for example, the above-mentioned method of the equation (1) orthe like, the image quality characteristic difference D between thecorrected image and the instructor image is calculated in accordancewith step ST4 in the image quality adjustment capability measurementmethod of the first exemplary embodiment (step ST14).

Subsequently, a determination is made as to whether the calculated imagequality characteristic difference D is less than or equal to a thresholdor whether the calculated image quality characteristic difference D is aminimum value (step ST15). When the result is NO, the processes of stepST12 to step ST14 are repeated. On the other hand, when the result isYES, the correction parameters obtained when the image qualitycharacteristic difference D is less than or equal to the threshold or isa minimum value is output as the optimum correction parameters which aretarget correction parameters by which the desired image qualities can beachieved (step ST16).

In that manner, according to the present exemplary embodiment, theevaluation images and the corresponding instructor images are provided,and the correlation function between the differences in the amount ofimage quality characteristic of the images and the people's imagequality adjustment capability values is calculated. Then, in order toobtain the desired image qualities of an arbitrarily input image, thedifference value between the amount of image quality characteristic ofthe corrected image, which is obtained after the image process of theinput image, and the amount of image quality characteristic of theinstructor image is calculated. Subsequently, with the use of thecorrelation function between the differences in the amount of imagequality characteristic and the people's image quality adjustmentcapability values, the target correction parameters are determined toobtain the desired image qualities. Then, the image process is appliedto the input image.

Therefore, according to the present exemplary embodiment, the imagequalities set in the color image device and the color image processingsystem can be automatically adjusted to the desired image qualitieswhich a person subjectively perceives.

Fifth Exemplary Embodiment

The following describes an image quality adjustment device 102 accordingto a fifth exemplary embodiment of the present invention, with referenceto FIG. 9.

FIG. 9 is a block diagram illustrating the image quality adjustmentdevice 102 according to the present exemplary embodiment. The imagequality adjustment device 102 shown in the diagram uses the imagequality adjustment method of the fourth exemplary embodiment, and is adevice to automatically produce the optimum correction parameters usedto adjust the image qualities of color images or the color image systemto the desired image qualities that a person subjectively perceives.

The image quality adjustment device 102 includes an evaluation imagestorage memory 1, an image processing section 2, a correction parametergeneration section 8, a corrected image storage memory 9, an instructorimage storage memory 5, an image quality characteristic differencecalculation section 6, and an optimum correction parameter determinationsection 10, which is a target correction parameter determinationsection.

The evaluation image storage memory 1 stores the evaluation image. Theimage processing section 2 performs an image process to adjust the imagequalities of the evaluation image and produces the corrected image. Thecorrection parameter generation section 8 generates the correctionparameters used in the image process of the image processing section 2.The corrected image storage memory 9 stores the corrected image. Theinstructor image storage memory 5 stores the instructor image, which isa target for the evaluation image. The image quality characteristicdifference calculation section 6 calculates the image qualitycharacteristic difference D between the corrected image and theinstructor image. The optimum correction parameter determination section10 runs the correction parameter generation section 8 until the imagequality characteristic difference D becomes a minimum value or less thanor equal to a threshold, and outputs the correction parameters, whichare obtained when the image quality characteristic difference D is aminimum value or is less than or equal to the threshold, as the optimumcorrection parameters which are target correction parameters by whichthe desired image qualities can be achieved.

The image quality adjustment device 102 can be realized by a computer.The components constituting the image quality adjustment device 102,including the evaluation image storage memory 1, the image processingsection 2, the correction parameter generation section 8, the correctedimage storage memory 9, the instructor image storage memory 5, the imagequality characteristic difference calculation section 6, and the optimumcorrection parameter determination section 10, can be realized as aprogram that the processing unit of the computer (CPU) executes torealize the above-mentioned functions. The components constituting theimage quality adjustment device 102 can be realized by a computer and asa program.

The following describes the operation of the image quality adjustmentdevice 102.

First, the image quality adjustment device 102 stores in advance theevaluation image and the instructor image, which is a target for theevaluation image, in the evaluation image storage memory 1 and theinstructor image storage memory 5, respectively.

Then, the correction parameter generation section 8 generates thecorrection parameters used in the image process to correct the imagequalities of the evaluation image.

Subsequently, the image processing section 2 performs the image processfor the evaluation image using the correction parameters generated bythe correction parameter generation section 8 to produce the correctedimage, and stores the corrected image in the corrected image storagememory 9.

Then, using, for example, the above-mentioned method of the equation (1)or the like, the image quality characteristic difference calculationsection 6 calculates the image quality characteristic difference Dbetween the corrected image stored in the corrected image storage memory9 and the corresponding instructor image stored in the instructor imagestorage memory 5 in accordance with step ST4 in the image qualityadjustment capability measurement method of the first exemplaryembodiment.

Subsequently, the optimum correction parameter determination section 10runs the correction parameter generation section 8 until the imagequality characteristic difference D becomes less than or equal to thethreshold or a minimum value. When the image quality characteristicdifference D becomes less than or equal to the threshold or a minimumvalue, the optimum correction parameter determination section 10 outputsthe correction parameters obtained at that time as the optimumcorrection parameter.

In that manner, even in the present exemplary embodiment, like the fifthexemplary embodiment, the evaluation images and the correspondinginstructor images are provided, and the correlation function between thedifferences in the amount of image quality characteristic of the imagesand the people's image quality adjustment capability values iscalculated. Then, in order to obtain the desired image qualities of anarbitrarily input image, the difference value between the amount ofimage quality characteristic of the corrected image, which is obtainedafter the image process of the input image, and the amount of imagequality characteristic of the instructor image is calculated.Subsequently, with the use of the correlation function between thedifferences in the amount of image quality characteristic and thepeople's image quality adjustment capability values, the correctionparameters are determined to obtain the desired image qualities. Then,the image process is applied to the input image.

Therefore, according to the present exemplary embodiment, the imagequalities set in the color image device and the color image processingsystem can be automatically adjusted to the desired image qualitieswhich a person subjectively perceives.

Incidentally, the image quality adjustment device 102 may not beequipped with the corrected image storage memory 9: The corrected imagegenerated by the image processing section 2 may be directly input intothe image quality characteristic difference calculation section 6.

Moreover, the image quality adjustment device 102 can be applied to animage and image quality adjustment device which adjusts the imagequalities of an arbitrarily input image using the image processingsection 2 and the optimum correction parameters which are output fromthe image quality adjustment device 102.

Sixth Exemplary Embodiment

The following describes an image quality adjustment method according toa sixth exemplary embodiment of the present invention, with reference toFIG. 10.

According to the image quality adjustment method of the presentexemplary embodiment, the following processes (steps ST17 and ST18) areadded to the image quality adjustment method of the fourth exemplaryembodiment: calculating the image quality adjustment capability value Sfor the image quality characteristic difference D obtained when theoptimum correction parameters are output at step ST16, with the use ofthe correlation function (S=Fc(D)) between the image qualitycharacteristic differences D and the image quality adjustment capabilityvalues S obtained at step ST7 in the image quality adjustment capabilitymeasurement method of the first exemplary embodiment, and outputting theimage quality adjustment capability value S.

Therefore, according to the present exemplary embodiment, the optimumcorrection parameters are automatically produced to adjust the imagequalities of the color image device or color image system to the desiredimage qualities that a person subjectively perceives. In addition, theimage quality adjustment capability value, or the performance in imagequalities when the optimum correction parameters are applied, can bepresented.

Seventh Exemplary Embodiment

The following describes an image quality adjustment device 103 accordingto a seventh exemplary embodiment of the present invention, withreference to FIG. 11.

FIG. 11 is a block diagram illustrating the image quality adjustmentdevice 103 according to the present exemplary embodiment. The imagequality adjustment device 103 has the configuration of the image qualityadjustment device 102 to which the image quality adjustment capabilitydetermination section 7 of the image quality adjustment capabilitymeasurement device 100 is added.

The image quality adjustment device 103 can be realized by a computer.The components constituting the image quality adjustment device 103,including the evaluation image storage memory 1, the image processingsection 2, the correction parameter generation section 8, the correctedimage storage memory 9, the instructor image storage memory 5, the imagequality characteristic difference calculation section 6, the optimumcorrection parameter determination section 10, and the image qualityadjustment capability determination section 7, can be realized as aprogram that the processing unit of the computer (CPU) executes torealize the above-mentioned functions. The components constituting theimage quality adjustment device 103 can be realized by a computer and asa program.

The following describes the operation of the image quality adjustmentdevice 103. Here, the difference between the image quality adjustmentdevice 103 and the image quality adjustment device 102 is described.

In the image quality adjustment device 103, after the optimum correctionparameter determination section 10 determines the optimum correctionparameters, the image quality adjustment capability determinationsection 7 calculates the image quality adjustment capability value usingthe image quality characteristic difference, which is obtained when theoptimum correction parameters are calculated, and the correlationfunction between the image quality characteristic differences and theimage quality adjustment capability values.

Therefore, even in the present exemplary embodiment, like the sixthexemplary embodiment, the optimum correction parameters areautomatically produced to adjust the image qualities of the color imagedevice or color image system to the desired image qualities that aperson subjectively perceives. In addition, the image quality adjustmentcapability value, or the performance in image qualities when the optimumcorrection parameters are applied, can be presented.

Incidentally, the image quality adjustment device 103 may not beequipped with the corrected image storage memory 9: The corrected imagegenerated by the image processing section 2 may be directly input intothe image quality characteristic difference calculation section 6.

Moreover, the image quality adjustment device 103 can be applied to animage and image quality adjustment device which adjusts the imagequalities of an arbitrarily input image using the image processingsection 2 and the optimum correction parameters which are output fromthe image quality adjustment device 103.

Eighth Exemplary Embodiment

The following describes an image quality adjustment capability trainingmethod according to an eighth exemplary embodiment of the presentinvention, with reference to FIG. 12.

According to the present exemplary embodiment, the image qualityadjustment capability training method contains the processes of stepsST1 to ST8 (see FIG. 1) of the image quality adjustment capabilitymeasurement method of the first exemplary embodiment, and the followingprocess (step ST9) between steps ST7 and ST8: Controlling the user'soperation of adjusting the image qualities (step ST6) in accordance withthe image quality adjustment capability value obtained at step ST7.

According to the method, after the processes of step ST1 to ST7 areperformed in a similar way to the first exemplary embodiment, the user'simage quality adjustment capability value obtained at step ST7 iscompared with a preset threshold (step ST9). As a result, when theuser's image quality adjustment capability value is, for example, lessthan the threshold (NO), the process of step ST6 is retried to promptthe user to continue the image quality adjustment operation. When theimage quality adjustment capability value is greater than the threshold(YES), the user is encouraged to end the image quality adjustmentoperation, and control is performed at the subsequent step SP8 to outputthe image quality adjustment capability value obtained at that time.

Therefore, according to the present exemplary embodiment, the person'simage quality adjustment capability, the capability to subjectivelyimprove the image qualities of the color image device or color imagesystem, can be improved.

Ninth Exemplary Embodiment

The following describes an image quality adjustment capability trainingdevice 104 according to a ninth exemplary embodiment of the presentinvention, with reference to FIG. 13.

According to the present exemplary embodiment, the image qualityadjustment capability training device 104 shown in FIG. 13 uses theimage quality adjustment capability training method of the eighthexemplary embodiment, and has the configuration of the image qualityadjustment capability measurement device 100 of the second exemplaryembodiment (FIG. 6) to which an image quality adjustment operationcontrol section 11 is added.

The image quality adjustment capability training device 104 can berealized by a computer. The components constituting the image qualityadjustment capability training device 104, including the evaluationimage storage memory 1, the image processing section 2, the imagepresentation section 3, the parameter control section 4, the instructorimage storage memory 5, the image quality characteristic differencecalculation section 6, the image quality adjustment capabilitydetermination section 7, and the image quality adjustment operationcontrol section 11, can be realized as a program that the processingunit of the computer (CPU) executes to realize the above-mentionedfunctions. The components constituting the image quality adjustmentcapability training device 104 can be realized by a computer and as aprogram.

The following describes the operation of the image quality adjustmentcapability training device 104. Here, the difference between the imagequality adjustment capability training device 104 and the image qualityadjustment capability measurement device 100 is described.

In the image quality adjustment capability training device 104, afterthe image quality adjustment capability determination section 7determines the user's image quality adjustment capability value, theimage quality adjustment operation control section 11 makes adetermination as to whether to allow the user to continue the imagequality adjustment operation or force the user to end the image qualityadjustment operation in accordance with the image quality adjustmentcapability value.

For example, when the user's image quality adjustment capability valuedetermined by the image quality adjustment capability determinationsection 7 is less than a threshold, the image quality adjustmentoperation control section 11 prompts the user to continue the imagequality adjustment operation.

Then, when the image quality adjustment capability value exceeds thethreshold, the image quality adjustment operation control section 11forces the user to end the image quality adjustment operation, and thenoutputs the image quality adjustment capability value obtained at thattime.

Therefore, even in the present exemplary embodiment, like the eighthexemplary embodiment, the person's image quality adjustment capability,the capability to subjectively improve the image qualities of the colorimage device or color image system, can be improved.

Incidentally, if each process (function) of the above-mentionedcomponents can be realized, each device of the above-mentioned exemplaryembodiments is not limited to a specific one in terms of physicalconfiguration of the device, and hardware and software structures insidethe device. For example, each of the following structures is applicable:a structure in which individual circuits, units, or program componentslike program modules are independently formed for each component; astructure in which a plurality of components is put together into onecircuit or unit. Depending on limitations of the function, usage or thelike of the actually used device, the above structures may be subjectedto selection, change, modification, or the like. Moreover, the operationmethod of a device that performs similar processes to those of eachfunction of the above-mentioned components is also within the scope ofthe present invention.

Moreover, at least part of each function of the above-mentionedcomponents may be realized by software processing by a computerconsisting of a processing device such as a microprocessor including aCPU. In this case, the program that causes the computer to function iswithin the scope of the present invention. The program is not limited tothose that the CPU can directly execute. The program includes sourceprograms, compressed programs, encrypted programs, and other kinds ofprograms. Moreover, the program can be provided in any of the followingforms: a program that operates in conjunction with a control programsuch as OS (Operating System), which takes overall control of thedevice, and firmware; an application program incorporated in part of thecontrol program to operate integrally; software components (softwaremodules) and the like constituting the control program. Furthermore, ifthe program is applied to a device having a communication function tocommunicate with an external device via a wireless or wired line, theprogram can be downloaded for example from an external node, such asserver, connected to the line and installed in a recording medium insidethe device before being used. Depending on the function, usage or thelike of the actually used device, the above structures may be subjectedto selection, change, modification, or the like.

Furthermore, a computer-readable recording medium on which theabove-mentioned program is recorded is within the scope of the presentinvention. In this case, each of the following recording media isapplicable: a stationary recording medium, which is fixed in the devicefor use; a portable recording medium that a user can carry.

The above has described the present invention with reference to theabove exemplary embodiments. However, the present invention is notlimited to the above exemplary embodiments. It should be understood bythose skilled in the art that various modifications may occur in theconfiguration or details of the present invention insofar as they arewithin the scope of the present invention.

The present application claims priority from Japanese Patent ApplicationNo. 2007-115611 filed on Apr. 25, 2007, the entire contents of whichbeing incorporated herein by reference.

INDUSTRIAL APPLICABILITY

The present invention can be applied to a function which measures theimage quality adjustment capability of a person or color image systemadjusting the image qualities of the color image device or color imageprocessing system. Moreover, the present invention can be applied to afunction which adjusts the image qualities of the color image device orcolor image processing system to the desired image qualities which aperson subjectively perceives. Furthermore, if the present invention isin the form of programs running on a computer system, the presentinvention can be applied to an arbitrary color image device or colorimage processing system as image quality measurement software, imagequality measurement utility, image quality adjustment software, or imagequality adjustment utility.

1. An image quality adjustment capability measurement method comprisingthe steps of: using an instructor image serving as a target for theimage qualities of an evaluation image and a correlation functionbetween image quality characteristic differences and image qualityadjustment capability values, the instructor image and the correlationfunction being obtained in advance; inputting a corrected image obtainedafter the image qualities of the evaluation image are adjusted;calculating the image quality characteristic difference between thecorrected image and the instructor image; and calculating the imagequality adjustment capability value from the correlation function andthe image quality characteristic difference.
 2. The image qualityadjustment capability measurement method according to claim 1, whereinusing the instructor image and the correlation function means: using theevaluation image, a first corrected image obtained after the imagequalities of the evaluation image are adjusted and evaluated in terms ofsubjective image quality, and an instructor image serving as a targetfor the image qualities of the evaluation image, the evaluation image,the first corrected image, and the instructor image being obtained inadvance; calculating the image quality adjustment capability value forthe first corrected image the subjective image qualities of which areevaluated; calculating the image quality characteristic differencebetween the first corrected image and the instructor image; and using acorrelation function between the image quality characteristic differenceand the image quality adjustment capability value calculated from theimage quality characteristic difference and the image quality adjustmentcapability value.
 3. An image quality adjustment capability measurementmethod comprising the steps of: using a first corrected image obtainedafter the image qualities of an evaluation image are adjusted andevaluated in terms of subjective image quality and an instructor imageserving as a target for the image qualities of the evaluation image, thefirst corrected image and the instructor image being obtained inadvance; calculating an image quality adjustment capability value forthe first corrected image; calculating an image quality characteristicdifference between the first corrected image and the instructor image,and acquiring a correlation function between the image qualitycharacteristic difference and the image quality adjustment capabilityvalue; acquiring a second corrected image by letting a user whose imagequality adjustment capability is to be measured adjust the imagequalities of the evaluation image; and calculating the image qualitycharacteristic difference between the second corrected image and theinstructor image, and calculating the user's image quality adjustmentcapability value from the correlation function and the image qualitycharacteristic difference.
 4. An image quality adjustment capabilitymeasurement method comprising the steps of: acquiring first correctedimages obtained after the image qualities of a plurality of evaluationimages are adjusted; performing subjective evaluation on the imagequalities of the first corrected images; calculating an image qualityadjustment capability value from the results of subjective evaluation onthe image qualities of the first corrected images; calculating the imagequality characteristic differences between the first corrected imagesand instructor images serving as targets for the image qualities of theevaluation images, and acquiring a correlation function between theimage quality characteristic difference and the image quality adjustmentcapability values; acquiring second corrected images by letting a userwhose image quality adjustment capability is to be measured adjust theimage qualities of the evaluation images; and calculating the imagequality characteristic differences between the second corrected imagesand the instructor images, and calculating the user's image qualityadjustment capability value from the correlation function and the imagequality characteristic differences.
 5. An image quality adjustmentcapability measurement device comprising: a section that uses a givencorrelation function between image quality characteristic differencesand image quality adjustment capability values; a corrected image inputsection that inputs a corrected image obtained after the image qualitiesof an evaluation image are adjusted; an instructor image storage memorythat stores an instructor image serving as a target for the imagequalities of the evaluation image; an image quality characteristicdifference calculation section that calculates the image qualitycharacteristic difference between the corrected image and the instructorimage; and an image quality adjustment capability determination sectionthat calculates the image quality adjustment capability value from thecorrelation function and the image quality characteristic difference. 6.An image quality adjustment capability measurement device comprising: asection that uses a given correlation function between image qualitycharacteristic differences and image quality adjustment capabilityvalues; an evaluation image storage memory that stores an evaluationimage; an image processing section that generates a corrected image byletting a user whose image quality adjustment capability is to bemeasured adjust the image qualities of the evaluation image; an imagepresentation section that presents the evaluation image and thecorrected image to the user; an instructor image storage memory thatstores an instructor image serving as a target for the image qualitiesof the evaluation image; an image quality characteristic differencecalculation section that calculates the image quality characteristicdifference between the corrected image and the instructor image; and animage quality adjustment capability determination section thatcalculates the user's image quality adjustment capability value from thecorrelation function and the image quality characteristic difference. 7.An image quality adjustment method comprising the steps of: using agiven evaluation image, a given instructor image serving as a target forthe image qualities of the evaluation image, and a given correlationfunction between image quality characteristic differences and imagequality adjustment capability values; generating correction parametersused in an image process to correct the image qualities of theevaluation image; generating a corrected image by performing the imageprocess for the evaluation image using the correction parameters;calculating the image quality characteristic difference between thecorrected image and the instructor image; determining target correctionparameters from the correction parameters using the image qualitycharacteristic difference and the correlation function to obtain thedesired image qualities; and correcting the image qualities of anarbitrarily input image using the image process and the targetcorrection parameters.
 8. The image quality adjustment method accordingto claim 7, wherein determining the target correction parametersincludes setting a target value for adjusting the desired imagequalities.
 9. An image quality adjustment device comprising: a sectionthat uses a given correlation function between image qualitycharacteristic differences and image quality adjustment capabilityvalues; an evaluation image storage memory that stores an evaluationimage; a correction parameter generation section that generatescorrection parameters used in an image process to adjust the imagequalities of the evaluation image; an image processing section thatgenerates a corrected image by performing the image process for theevaluation image using the correction parameters; an instructor imagestorage memory that stores an instructor image serving as a target forthe image qualities of the evaluation image; an image qualitycharacteristic difference calculation section that calculates the imagequality characteristic difference between the corrected image and theinstructor image; a target correction parameter determination sectionthat determines target correction parameters from the correctionparameters using the image quality characteristic difference and thecorrelation function to obtain the desired image qualities; and an imagecorrection section that corrects the image qualities of an arbitrarilyinput image using the image process and the target correctionparameters.
 10. The image quality adjustment device according to claim9, wherein the target correction parameter determination sectionincludes a section that sets a target value for adjusting the desiredimage qualities.
 11. An image quality adjustment capability measurementprogram causing a computer to execute: a process of using a givencorrelation function between image quality characteristic differencesand image quality adjustment capability values; a process of inputting acorrected image obtained after the image qualities of an evaluationimage are adjusted; a process of storing an instructor image serving asa target for the image qualities of the evaluation image; a process ofcalculating the image quality characteristic difference between thecorrected image and the instructor image; and a process of calculatingthe image quality adjustment capability value from the correlationfunction and the image quality characteristic difference.
 12. An imagequality adjustment capability measurement program causing a computer toexecute: a process of using a given correlation function between imagequality characteristic differences and image quality adjustmentcapability values; a process of storing an evaluation image; an imageprocess of generating a corrected image by letting a user whose imagequality adjustment capability is to be measured adjust the imagequalities of the evaluation image; a process of presenting theevaluation image and the corrected image to the user; a process ofallowing the user to control parameters used in the image process; aprocess of storing an instructor image serving as a target for the imagequalities of the evaluation image; a process of calculating the imagequality characteristic difference between the corrected image and theinstructor image; and a process of calculating the user's image qualityadjustment capability value from the correlation function and the imagequality characteristic difference.
 13. An image quality adjustmentprogram causing a computer to execute: a process of using a givencorrelation function between image quality characteristic differencesand image quality adjustment capability values; a process of storing anevaluation image; a process of generating correction parameters used inan image process to adjust the image qualities of the evaluation image;a process of generating a corrected image by performing the imageprocess for the evaluation image using the correction parameters; aprocess of storing an instructor image serving as a target for the imagequalities of the evaluation image; a process of calculating the imagequality characteristic difference between the corrected image and theinstructor image; a process of determining target correction parametersfrom the correction parameters using the image quality characteristicdifference and the correlation function to obtain the desired imagequalities; and a process of correcting the image qualities of anarbitrarily input image using the image process and the targetcorrection parameters.
 14. The image quality adjustment programaccording to claim 13, wherein the process of determining the targetcorrection parameters includes a process of setting a target value foradjusting the desired image qualities.
 15. An image quality adjustmentcapability training method comprising the steps of: using an instructorimage serving as a target for the image qualities of an evaluation imageand a correlation function between image quality characteristicdifferences and image quality adjustment capability values, theinstructor image and the correlation function being obtained in advance;acquiring a corrected image by letting a user whose image qualityadjustment capability is to be measured adjust the image qualities ofthe evaluation image; calculating the image quality characteristicdifference between the corrected image and the instructor image, andcalculating the user's image quality adjustment capability value fromthe correlation function and the image quality characteristicdifference; and controlling an image quality adjustment operation inwhich the user adjusts the image qualities of the evaluation image toobtain the corrected image.
 16. An image quality adjustment capabilitytraining method comprising the steps of: using a first corrected imageobtained after the image qualities of an evaluation image are adjustedand evaluated in terms of subjective image quality and an instructorimage serving as a target for the image qualities of the evaluationimage, the first corrected image and the instructor image being obtainedin advance; calculating an image quality adjustment capability value forthe first corrected image evaluated in terms of the subjective imagequality; calculating an image quality characteristic difference betweenthe corrected image and the instructor image, and acquiring acorrelation function between the image quality characteristic differenceand the image quality adjustment capability value; acquiring a secondcorrected image by letting a user whose image quality adjustmentcapability is to be measured adjust the image qualities of theevaluation image; calculating the image quality characteristicdifference between the second corrected image and the instructor image,and calculating the user's image quality adjustment capability valuefrom the correlation function and the image quality characteristicdifference; and controlling an image quality adjustment operation inwhich the user adjusts the image qualities of the evaluation image toobtain the second corrected image.
 17. An image quality adjustmentcapability training device comprising: a section that uses a givencorrelation function between image quality characteristic differencesand image quality adjustment capability values; an evaluation imagestorage memory that stores an evaluation image; an image processingsection that generates a corrected image by letting a user whose imagequality adjustment capability is to be measured adjust the imagequalities of the evaluation image; an instructor image storage memorythat stores an instructor image serving as a target for the imagequalities of the evaluation image; an image quality characteristicdifference calculation section that calculates the image qualitycharacteristic difference between the corrected image and the instructorimage; an image quality adjustment capability determination section thatcalculates the user's image quality adjustment capability value from thecorrelation function and the image quality characteristic difference;and an image quality adjustment operation control section that controlsan image quality adjustment operation in which the user adjusts theimage qualities of the evaluation image to generate the corrected image.18. An image quality adjustment capability training program causing acomputer to execute: a process of using a given correlation functionbetween image quality characteristic differences and image qualityadjustment capability values; a process of storing an evaluation image;an image process of generating a corrected image by letting a user whoseimage quality adjustment capability is to be measured adjust the imagequalities of the evaluation image; a process of presenting theevaluation image and the corrected image to the user; a process ofallowing the user to control parameters used in the image process; aprocess of storing an instructor image serving as a target for the imagequalities of the evaluation image; a process of calculating the imagequality characteristic difference between the corrected image and theinstructor image; a process of calculating the user's image qualityadjustment capability value from the correlation function and the imagequality characteristic difference; and a process of controlling an imagequality adjustment operation in which the user adjusts the imagequalities of the evaluation image to generate the corrected image.